通过优化的并发霍夫变换在透视图像中自动分割腰椎

Yalin Zheng, M. S. Nixon, R. Allen
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引用次数: 9

摘要

我们展示了一种新方法如何同时自动检测椎骨的位置和边界,减轻了其他方法中遇到的许多问题。首先,我们利用相位一致性来解决光照变量DVF图像边缘检测中阈值选择的困难。然后,我们的新霍夫变换方法应用于确定运动椎骨,同时。我们通过遗传算法进行优化(因为没有遗传算法,提取移动的多个椎骨在计算上是令人生畏的)。我们的结果表明,这种新方法确实可以提供位置和旋转的提取,这似乎是足够的质量,以帮助治疗和诊断脊柱疾病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic lumbar vertebrae segmentation in fluoroscopic images via optimised concurrent Hough transform
We show how a new approach can automatically detect the positions and borders of vertebrae concurrently, relieving many of the problems experienced in other approaches. First, we use phase congruency to relieve the difficulty associated with threshold selection in edge detection of the illumination variant DVF images. Then, our new Hough transform approach is applied to determine the moving vertebrae, concurrently. We include optimisation via a genetic algorithm (as without it the extraction of moving multiple vertebrae is computationally daunting). Our results show that this new approach can indeed provide extractions of position and rotation which appear to be of sufficient quality to aid therapy and diagnosis of spinal disorders.
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